Introducing Data Science
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Introducing Data Science
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Author : Davy Cielen
language : en
Publisher: Simon and Schuster
Release Date : 2016-05-02
Introducing Data Science written by Davy Cielen and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-02 with Computers categories.
Summary Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started. About the Book Introducing Data ScienceIntroducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You’ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You’ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. What’s Inside Handling large data Introduction to machine learning Using Python to work with data Writing data science algorithms About the Reader This book assumes you're comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required. About the Authors Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors. Table of Contents Data science in a big data world The data science process Machine learning Handling large data on a single computer First steps in big data Join the NoSQL movement The rise of graph databases Text mining and text analytics Data visualization to the end user
Introducing Data Science For Beginners 2025 Learn Data Analysis Visualization Machine Learning Basics
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Author : A. Ali
language : en
Publisher: Code Academy
Release Date :
Introducing Data Science For Beginners 2025 Learn Data Analysis Visualization Machine Learning Basics written by A. Ali and has been published by Code Academy this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Introducing Data Science for Beginners 2025 is your essential guide to understanding the fundamentals of data science, even if you have no prior experience. This beginner-friendly book breaks down core concepts such as data analysis, visualization, statistics, and the basics of machine learning. With real-world examples and simplified explanations, it helps you build a strong foundation in Python, data handling, and decision-making through data. Whether you're a student, professional, or enthusiast, this book provides the perfect starting point to enter the world of data science with confidence.
Introduction To Data Science And Machine Learning
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Author : Keshav Sud
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-03-25
Introduction To Data Science And Machine Learning written by Keshav Sud and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-25 with Computers categories.
Introduction to Data Science and Machine Learning has been created with the goal to provide beginners seeking to learn about data science, data enthusiasts, and experienced data professionals with a deep understanding of data science application development using open-source programming from start to finish. This book is divided into four sections: the first section contains an introduction to the book, the second covers the field of data science, software development, and open-source based embedded hardware; the third section covers algorithms that are the decision engines for data science applications; and the final section brings together the concepts shared in the first three sections and provides several examples of data science applications.
A Simple Introduction To Data Science
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Author : Lars Nielsen
language : en
Publisher: New Street Communications, LLC
Release Date : 2015-04-10
A Simple Introduction To Data Science written by Lars Nielsen and has been published by New Street Communications, LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-10 with categories.
Taking up where the bestselling "A Simple Introduction to Data Science" leaves off, Lars Nielsen's "A Simple Introduction to Data Science, BOOK TWO" expands on elementary concepts introduced in the first volume while at the same time embracing several new and key topics. Coverage includes the art and practice of introducing Data Science to the culture of the enterprise ... Data Science ethics and privacy concerns ... key concepts in data visualization ... the role of Artificial Intelligence, Machine Learning, and Deep Learning ... Data Curation and the "Tribal Knowledge" problem ... Hadoop, R, and Python ... and discussion of how the Data Scientist role will evolve in future.
Introduction To Data Science
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Author : Laura Igual
language : en
Publisher: Springer Nature
Release Date : 2024-04-12
Introduction To Data Science written by Laura Igual and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-12 with Computers categories.
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the interdisciplinary field of data science. The coverage spans key concepts from statistics, machine/deep learning and responsible data science, useful techniques for network analysis and natural language processing, and practical applications of data science such as recommender systems or sentiment analysis. Topics and features: Provides numerous practical case studies using real-world data throughout the book Supports understanding through hands-on experience of solving data science problems using Python Describes concepts, techniques and tools for statistical analysis, machine learning, graph analysis, natural language processing, deep learning and responsible data science Reviews a range of applications of data science, including recommender systems and sentiment analysis of text data Provides supplementary code resources and data at an associated website This practically-focused textbook provides an ideal introduction to the field for upper-tier undergraduate and beginning graduate students from computer science, mathematics, statistics, and other technical disciplines. The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses.
Data Science For Beginners
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Author : Prof John Smith
language : en
Publisher: Independently Published
Release Date : 2018-12-12
Data Science For Beginners written by Prof John Smith and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with categories.
DATA SCIENCE FOR BEGINNERS Introduction to Data Science: Python,Coding, Application, Statistics,Decision Tree, Neural Network, and Linear Algebra WHAT THIS BOOK WILL DO FOR YOU We will talk about what is the need for data science and then what exactly is data science some definitions and understand. The differences between data science and business intelligence,Then we will talk about the prerequisites for learning data science, and then what does the data scientist do. What are the activities performed by a data scientist as a part of his daily life and then we will talk about the data science lifecycle witha quick example and briefly touch upon the demand or ever-increasing demand for data scientist. Benefits of Data science Data Science: Automobile Data science: Aviation Data science can also be used to make promotional offers. Chapters Data science: Its Advantage Data science: Its Definition Process in data science Difference between business intelligence and data science Prerequisites for data science Machine learning. Data science: Tools and skills in data science. Data Science: Machine-learning algorithms Data science: Life cycle of a data science Data science: Exploratory data analysis Data science: Techniques for exploratory data analysis
Introduction To Data Science
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Author : Laura Igual
language : en
Publisher: Springer
Release Date : 2017-02-22
Introduction To Data Science written by Laura Igual and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-22 with Computers categories.
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
An Introduction To Data Science
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Author : Jeffrey S. Saltz
language : en
Publisher: SAGE Publications
Release Date : 2017-08-25
An Introduction To Data Science written by Jeffrey S. Saltz and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-25 with Social Science categories.
An Introduction to Data Science is an easy-to-read, gentle introduction for advanced undergraduate, certificate, and graduate students coming from a wide range of backgrounds into the world of data science. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using the R programming language and RStudio® from the ground up. Short chapters allow instructors to group concepts together for a semester course and provide students with manageable amounts of information for each concept. By taking students systematically through the R programming environment, the book takes the fear out of data science and familiarizes students with the environment so they can be successful when performing advanced functions. The authors cover statistics from a conceptual standpoint, focusing on how to use and interpret statistics, rather than the math behind the statistics. This text then demonstrates how to use data effectively and efficiently to construct models, predict outcomes, visualize data, and make decisions. Accompanying digital resources provide code and datasets for instructors and learners to perform a wide range of data science tasks.
A Hands On Introduction To Data Science
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Author : Chirag Shah
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-02
A Hands On Introduction To Data Science written by Chirag Shah and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Business & Economics categories.
An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.
Empowering Early Education With Computational Thinking Ai And Stem
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Author : Kalogiannakis, Michail
language : en
Publisher: IGI Global
Release Date : 2024-11-08
Empowering Early Education With Computational Thinking Ai And Stem written by Kalogiannakis, Michail and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-08 with Education categories.
Empowering early education with computational thinking, artificial intelligence (AI), and science, technology, engineering, and mathematics (STEM) is transforming the way students engage with the learning process. As the educational field develops, the integration of these fields in early childhood curricula enhances critical thinking and problem-solving skills while fostering creativity and collaboration among students. By introducing foundational concepts of computational thinking and AI at a young age, educators can cultivate a generation of innovators who are equipped to navigate complex challenges and contribute to society. Further research into effective integration may prepare children for future academic pursuits while instilling a personal interest in learning, ensuring students can thrive in a technological world. Empowering Early Education With Computational Thinking, AI, and STEM explores the integration of computational thinking, AI, and STEM into early education environments. It provides comprehensive guidance on effectively introducing computational thinking, coding skills, and STEM concepts to young learners, offering practical strategies and resources for educators. This book covers topics such as curriculum development, educational technologies, and gamification, and is a useful resource for educators, teachers, administrators, scientists, computer engineers, academicians, and researchers.